FDA clearance in medical AI continues to serve as an entry ticket rather than a guarantee of clinical return on investment. According to a survey of 215 Society of Breast Imaging members published in Clinical Imaging, roughly half of practitioners already deploy FDA-cleared AI tools for breast cancer screening, with another 11% preparing to adopt them. Yet, as lead author Joud Almogati of UC San Diego Health points out, practically none of these clinicians treat AI as a decisive diagnostic partner.
The real-world gap between vendor promises and daily radiology workflows is stark. While 59% of surveyed clinicians expected AI to reduce false-positive recall rates, only 35% observed that benefit in clinical practice. The workload relief narrative collapses just as quickly: 56% anticipated meaningful protection against burnout, but only 29% felt any tangible reduction in operational strain.
The most glaring disconnect sits in invasive intervention rates. Although 36% of radiologists expected software assistance to curb unnecessary biopsies, a meager 9% saw that outcome materialize. High licensing costs and absent institutional infrastructure leave these models operating as expensive, advisory second opinions—leaving the core bottlenecks of radiologist fatigue and diagnostic uncertainty completely unresolved.